This talk will address the question of how to enable a much more agile data provisioning model for business units and data scientists. We’re in a mode shift where data unlocks new growth, and almost every Fortune 1000 company is scrambling to architect a new platform to enable data to be stored, shared and analyzed for competitive advantage. Many companies are finding that this shift requires major rethinking of how systems should be architected (and scaled) to enable agile, self-service access to critical data.
In this session we’ll discuss strategies for building agile big-data clouds that make it much faster and easier for data scientists to discover, provision and analyze data. We’ll discuss where and how new technologies (both vendor and OSS) fit into this model.
We will also discuss changes in application architectures as big-data begins to play a role in online applications, incorporating many big-data techniques to deliver consumer-targeted content. This new “real-time” analytics category is growing fast and several new data systems are enabling this shift. We’ll review which players and technologies in the NoSQL community are helping drive this architecture.
Performance Geek. Application Infrastructure CTO at VMware. Car enthusiast. Photographer. bio from Twitter
5pm Big Data and Big Analytics: SciDB is not Hadoop by Paul Brown
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